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The carbon oxides (CO2 and CO) in the insulating oil of power transformers come from the thermal aging of cellulosic insulating paper; the CO2/CO ratio can reflect the aging state of cellulosic insulating paper. At present, the formation mechanisms of CO2 and CO in oil-immersed power transformers are still unclear. In this article, the ReaxFF reaction force field is used to simulate the thermal aging process of cellulosic insulating paper, and the main reaction pathways of CO2 and CO molecules formed by cellulose pyrolysis are obtained. The study finds that the amount of CO2 and CO generated is related to temperature. When the pyrolysis temperature continues to rise, the amount of CO2 generated shows a downward trend, while the amount of CO generated continues to increase, and the CO2/CO ratio continues to decrease. The simulation results are consistent with the previous experimental results. Through pathway tracking, it is found that the CO2 and CO molecules are mainly derived from certain specific atoms of cellulose molecules. The COSMO-RS module is used to analyze the change trend of the solubility of CO2 and CO in insulating oil with temperature. The results show that the solubility of CO2 and CO decreases with the increase of insulating oil temperature, which provides theoretical support for accurate application of carbon oxides aging evaluation index at different temperatures. [ABSTRACT FROM AUTHOR]

Seamless integration of functional nanomaterials on paper can boost the functionality of paper-based flexible sensors and electronics. In this paper, we report the systematic study of a low-cost hydrothermal process for growing zinc oxide nanowires (ZnO NWs) on cellulose paper substrates. To control the competition between homogeneous and heterogeneous nucleation and obtain ZnO NWs with superior morphology and high growth efficiency, we tune the critical growth parameters including temperature, assistant chemicals, and seeding layer. We experimentally confirm the necessity of ammonium hydroxide as assistant chemical in the growth solution, and achieve a condition that generates the highest weight growth percentage of 40% in the tested range. We quantify the weight growth percentage of ZnO NWs over growth time, measure the electrical resistance of the ZnO-NW paper, and eventually establish an experimental guideline for preparing ZnO-NW paper with desired electrical property. To demonstrate potential applications of the ZnO-NW paper, we use the obtained ZnO-NW paper for sensing of ultraviolet light and mechanical touch. This paper provides experimental insights into hydrothermal growth of ZnO NWs on paper, and could further inspire novel utilization of ZnO-NW paper for flexible sensors and electronics. [ABSTRACT FROM PUBLISHER]

Oil soluble chemical markers such as methanol, ethanol and 2-furaldehyde for assessing the condition of insulating paper still present many challenges for an accurate interpretation in real transformers. Indeed, many conceptual parameters such as design (shell vs. core) or type of cooling are needed for a more accurate interpretation of the data. Moreover, similarly to water, the measured marker concentrations in oil are temperature-dependent, i.e. an existing partition phenomenon between the oil and the solid insulation modify the solubility of the markers, thus changing their apparent concentrations in the oil. Consequently, to follow the real trend of these species during the transformer?s service life, it is crucial to correct their concentrations at a specific temperature, as is done for the water content. Knowing these facts and in order to calibrate a predictive model, Hydro-Qu?bec decided to access equipment when dismantled, which enables a large amount of paper to be sampled from different sections of the windings. This allows for a more accurate representation of the transformer paper conditions in relation to transformer design. The paper condition obtained by measuring the degree of polymerization in accordance with the presence of chemical markers is a valuable process. We believe that it is possible to better understand the behavior of the paper insulation and to assess markers concentration thresholds using the oil analysis. This article discusses the recent experience in this field with specific cases. [ABSTRACT FROM AUTHOR]

Creatinine is a biochemical waste that is disseminated continually inside human blood. A synthetic polymer is developed in this study using Molecularly Imprinted Polymerization (MIP) technology with the precipitation polymerization method. The MIP polymer is used for finding the levels of creatinine from human serum samples with different creatinine concentrations. The MIP polymer is very selective to the specific adsorption of the molecules of creatinine. The produced MIP polymer is suitable for evaluating creatinine concentrations until 50 parts per million (ppm) that is thrice greater than the standard. The fabrication of chip-sized Micro-Electro-Mechanical-Systems (MEMS)-based interdigital (ID) sensors is described. The operation of the MEMS sensor is verified using the technique of Electrochemical Impedance Spectroscopy (EIS). The presented details of the development of MEMS ID sensor and creatinine specific MIP polymer are for detecting raised biotoxic waste levels, i.e. creatinine management is part of our research. The raised levels need monitoring by frequent pathological visits to those patients who have impaired kidney functioning. The complete system will be helpful for creatinine management at any time from home at a low cost. While early detection of an increase in creatinine and monitoring of kidney health to prevent further health-related complications are the goal of this research, results of up to 50 ppm are accessed. Until 50 ppm of MIP functionality is checked for confirming the MIP polymer adsorption of creatinine and the results are shown, which helps establish the sensing technology even if used for a patient with a high creatinine level. [ABSTRACT FROM AUTHOR]

Hydrogels are cross-linked polymer networks able to absorb or to release large amounts of water. The water uptake is associated with a considerable volume change but also with changes of optical properties like the refractive index. The swelling can be excited by a large spectrum of different physical (e.g. temperature, electrical voltage, magnetic field) and chemical factors (e.g. pH value, concentrations of chemical or biochemical species). The particular sensitivity can be adjusted by tailoring the composition of the hydrogel or via its functionalization. If the interaction between hydrogel and analyte to be measured is reversible then such hydrogels are becoming a promising candidate for miniaturized, cost-effective and inline-capable sensors. [ABSTRACT FROM AUTHOR]

Different wood-fibre based papers were characterized by dielectric spectroscopy, mechanical testing and microscopy. The data obtained were utilized to investigate the relationship between the chemistry, morphology and density of a paper and its permittivity and dielectric loss. The density strongly influences the dielectric response, but the response is not affected by the way the density has been achieved; by pressing the paper during drying or by mechanical treatment of the fibres before sheet preparation. The chemical composition of the pulp influences the polarization, dielectric loss and charge transport. It was found that paper-vacuum and paper-oil combinations can be represented by series-equivalent circuits. The permittivity of paper made from electrical grade kraft pulp, used in e.g. high voltage transformers, without any porosity is estimated to be 5.3 and tan δ to 0.01- 0.02 at 50 Hz and 70 °C. The lignin and hemicellulose content of the kraft pulp do not affect the real part of the permittivity significantly, but the dielectric losses increase with increasing lignin and hemicellulose content in both oil and vacuum at 50 Hz and 70 °C. [ABSTRACT FROM PUBLISHER]

Motivated by the fact that living cells use molecular circuits (i.e., a set of chemical reactions) for information processing, this paper investigates the problem of designing molecular circuits for demodulation. In our earlier work, we use a Markovian approach to derive a demodulator for diffusion-based molecular communication. The demodulation filters take the form of an ordinary differential equation, which computes the log-posteriori probability of a transmission symbol being sent. This paper considers the realization of these demodulation filters using molecular circuits assuming the transmission symbols are rectangular pulses of the same duration but different amplitudes, i.e., concentration modulation. This paper makes a number of contributions. First, we use time-scale separation and renewal theory to analytically derive an approximation of the demodulation filter from our earlier work. Second, we present a method to turn this approximation into a molecular circuit. By using simulations, we show that the output of the derived molecular circuit is approximately equal to the log-posteriori probability calculated by the exact demodulation filter if the log-posteriori probability is positive. Third, we demonstrate that a biochemical circuit in yeast behaves similarly to the derived molecular demodulation filter and is therefore a candidate for implementing the derived filter. [ABSTRACT FROM AUTHOR]

Titanium tetrachloride (TiCl4) is a well-known source of titanium (Ti) for the formation of titanium nitride (TiN) barrier material in the semiconductor interconnection process; however, the reaction of by-products with airborne molecules can cause unexpected pump trips and equipment breakdown from the by-product powder build-up. Plasma scrubbers are used to decompose by-products, but hydrogen chloride (HCl) and nitrogen oxides are produced during and after the process. The process mechanisms change when the temperature and applied power of the heat source change. In this paper, we study the influence of the reactor temperature and applied power to the heat source on the decomposition capacity of TiCl4 in a plasma pretreatment system (PPS). We examine the effect of the temperature and heat source power to understand the reaction mechanisms for the composition and decomposition of gaseous species with chemical reactions through simultaneous methods. We analyzed the system with computational fluid dynamics (CFD) and chemical kinetic simulation to investigate the changes of the system mechanism. Subsequently, we achieved results for the correlation between the temperature of the reactor, power applied to the heat source, composition and decomposition of species, and chemical reaction mechanisms. [ABSTRACT FROM AUTHOR]

At the 2006 IEEE International Conference on Systems of Systems Engineering, Boardman and Sauser presented a set of characteristics based on an integrative review of the literature. These characteristics are the foundation of the Boardman–Sauser system of systems (SoS) theory. We accept this theory as the basis of collaborative SoS and desire a means to validate this assertion. While numerous simulations have been published, the target SoS is usually a specific implementation. These specialized simulations produce results applicable primarily to the system under study but not necessarily SoS in general. Simulating the mathematical model of the Boardman–Sauser SoS theory in the form of an agent-based model produces results that can be compared with chemical reactions. This paper contends that the formation of molecules from atoms is an analog of systems forming any collaborative SoS, which we call our molecule organization model. The result is a supported logical argument that validates the Boardman–Sauser SoS theory as definitive of a generic SoS with behavior applicable to collaborative SoS. This paper seeks to provide a unique contribution to the SoS body of knowledge by increasing our understanding of collaboration in an SoS, so we may better understand their health, maintenance, replication, and evolution. [ABSTRACT FROM PUBLISHER]

The performance of a communication link can be improved by maximizing the mutual information between the input and output signals. This paper considers this maximization problem in a molecular communication link where both the transmitter and the receiver are molecular circuit. This general optimization is hard to solve. We simplify the problem by limiting to reactions with linear reaction rates and molecular circuits with a limited number of species. We derive an expression of mutual information and use it for numerical maximization. We show that our parameterized transmitter circuit is able to give mutual information that is close to upper bound obtained in our earlier work. [ABSTRACT FROM AUTHOR]

This paper considers a diffusion-based molecular communication system, where the transmitter uses reaction shift keying (RSK) as the modulation scheme. We focus on the demodulation of RSK signal at the receiver. The receiver consists of a front-end molecular circuit and a back-end demodulator. The front-end molecular circuit is a set of chemical reactions consisting of multiple chemical species. The optimal demodulator computes the posteriori probability of the transmitted symbols given the history of the observation. The derivation of the optimal demodulator requires the solution to a specific Bayesian filtering problem. The solution to this Bayesian filtering problem had been derived for a few specific molecular circuits and specific choice(s) of observed chemical species. The derivation of such solution is also lengthy. The key contribution of this paper is to present a general solution to this Bayesian filtering problem, which can be applied to any molecular circuit and any choice of observed species. [ABSTRACT FROM PUBLISHER]

Over the past decades, Chemical-induced Disease (CID) relations have attracted extensive attention in biomedical community, reflecting wide applications in biomedical research and healthcare field. However, prior efforts fail to make full use of the interaction between local and global contexts in biomedical document, and the derived performance needs to be improved accordingly. In this paper, we propose a novel framework for document-level CID relation extraction. More specifically, a stacked Hypergraph Aggregation Neural Network (HANN) layers are introduced to model the complicated interaction between local and global contexts, based on which better contextualized representations are obtained for CID relation extraction. In addition, the CID Relation Heterogeneous Graph is constructed to capture the information with different granularities and improve further the performance of CID relation classification. Experiments on a real-world dataset demonstrate the effectiveness of the proposed framework. [ABSTRACT FROM AUTHOR]

Chemical reactions are a prominent feature of molecular communication systems, with no direct parallels in wireless communications. While chemical reactions may be used inside the transmitter nodes, receiver nodes, or the communication medium, we focus on its utility in the medium in this paper. Such chemical reactions can be used to perform computation over the medium as molecules diffuse and react with each other (physical-layer computation). We propose the use of chemical reactions for the following purposes: 1) to reduce signal-dependent observation noise of receivers by reducing the signal density; 2) to realize molecular physical-layer network coding (PNC) by performing the natural XOR operation inside the medium; and 3) to reduce the inter-symbol interference (ISI) of other transmitters by canceling out the remaining molecules from previous transmissions. To make the ideas formal, we consider an explicit two-way relaying example with a transparent receiver (which has a signal-dependent noise). The proposed ideas are used to define a modulation scheme (which we call the PNC scheme). We compare the PNC with a previously proposed scheme for this problem, where the XOR operation is performed at the relay node (using a molecular logic gate). We call the latter, the straightforward network coding (SNC). It is observed that in addition to the simplicity of the proposed PNC scheme, it outperforms the SNC scheme especially when we consider ISI. [ABSTRACT FROM AUTHOR]

Circuit widths and nodes of semiconductor wafers have been continually shrinking down to less than 20 nm. Therefore, modern wafer fabs enforce extremely strict process control to prevent wafer quality failures. A wafer processing chamber is now frequently cleaned to remove residual chemicals and impurities. Yu et al. show that such cleaning operations significantly change the tool operation of single-armed cluster tools, and they suggest an idea of partial wafer loading to improve the tool throughput under cleaning requirements. However, little is known about how a dual-armed tool could be effectively scheduled when chamber cleaning exists. A dual-armed robot allows more flexible tool operational sequences, and hence, the scheduling problem becomes further complicated and challenging. In this paper, we propose a scheduling method by which the dual arms can be properly exploited for better tool productivity. We show that the suggested hybrid sequence significantly reduces the tool cycle time as compared to previously developed scheduling methods. Through this research, we conclude that the productivity gain of the dual arms against single arm is more significant when chambers are cleaned. Note to Practitioners—This paper is motivated by the scheduling issues of cluster tools with chamber cleaning requirements. Though an efficient scheduling method for single-armed cluster tools is presented by Yu et al., its performance is not sufficiently close to the optimal when a dual-armed robot is considered. More specifically, we cannot expect any productivity improvement from adopting a dual-armed robot, although it allows more flexible tool operations and is known to have higher throughput than a single-armed robot. Thus, we propose a novel scheduling method for dual-armed cluster tools that require chamber cleaning operations. The experimental results show that the suggested method achieves optimal tool throughput in most of the practical tool conditions. [ABSTRACT FROM AUTHOR]

In a diffusion-based molecular communication network, transmitters and receivers communicate by using signalling molecules (or ligands) in a fluid medium. This paper assumes that the transmitter uses different chemical reactions to generate different emission patterns of signalling molecules to represent different transmission symbols, and the receiver consists of receptors. When the signalling molecules arrive at the receiver, they may react with the receptors to form ligand-receptor complexes. Our goal is to study the demodulation in this setup assuming that the transmitter and receiver are synchronised. We derive an optimal demodulator using the continuous history of the number of complexes at the receiver as the input to the demodulator. We do that by first deriving a communication model which includes the chemical reactions in the transmitter, diffusion in the transmission medium and the ligand-receptor process in the receiver. This model, which takes the form of a continuous-time Markov process, captures the noise in the receiver signal due to the stochastic nature of chemical reactions and diffusion. We then adopt a maximum a posteriori framework and use Bayesian filtering to derive the optimal demodulator. We use numerical examples to illustrate the properties of this optimal demodulator. [ABSTRACT FROM PUBLISHER]

The identification of drug side-effects is considered to be an important step in drug design, which could not only shorten the time but also reduce the cost of drug development. In this paper, we investigate the relationship between the potential side-effects of drug candidates and their chemical structures. The preliminary Regularized Regression (RR) model for drug side-effects prediction has promising features in the efficiency of model training and the existence of a closed form solution. It performs better than other state-of-the-art methods, in terms of minimum accuracy and average accuracy. In order to dig inside how drug structure will associate with side effect, we further propose weighted GTS (Generalized T-Student Kernel: WGTS) SVM model from a structural risk minimization perspective. The SVM model proposed in this paper provides a better understanding of drug side-effects in the process of drug development. The usefulness of the WGTS model lies in the superior performance in a cross validation setting on 888 approved drugs with 1385 side-effects profiling from SIDER database. This work is expected to shed light on intriguing studies that predict potential un-identifying side-effects and suggest how we can avoid drug side-effects by the removal of some distinguished chemical structures. [ABSTRACT FROM AUTHOR]

Selective catalytic reduction (SCR) systems have been widely used to meet the emission regulations and two-cell SCR systems have shown the advantages of high NO $_{x}$ conversion efficiency and low NH $_{3}$ slip simultaneously. However, it is noteworthy that the catalyst performance of SCR device would degrade over the service time gradually. If the performance degrading is not well-compensated, the NO $_{x}$ conversion efficiency would reduce significantly. Different from detecting the aging issue in the laboratory, a practical method is to design an observer to estimate the aging factor online such that the urea injection can be modified accordingly. In this paper, we aim to construct an aging-factor observer for two-cell SCR systems. In order to reduce the algorithm computational load and guarantee the implementation performance, we propose a dual time-scale algorithm based on two-cell SCR model and unscented Kalman filter. There is a fast time scale and a slow time scale in the algorithm. Two simulation studies of constant aging factor and time-varying aging factor are investigated in the simulation environment of MATLAB/SIMULINK. The simulation results indicate that the proposed dual time-scale observer works well under different conditions and the calculational load is reduced significantly. [ABSTRACT FROM AUTHOR]

Over the past decade, ion-sensitive field-effect transistors (ISFETs) have played a major role in enabling the fabrication of fully integrated CMOS-based chemical sensing systems. This has allowed several new application areas, with the most promising being the fields of ion imaging and full genome sequencing. This paper reviews the new trends in front-end topologies toward the design of ISFET sensing arrays in CMOS for these new applications. More than a decade after the review of the ISFET by Bergveld which summarized the state of the art in terms of device and early readout circuity, we describe the evolution in terms of device macromodel and identify the main sensor challenges for current designers. We analyze the techniques that have been reported for both ISFET instrumentation and compensation, and conclude that topologies are focusing on device adaptation for offset and drift cancellation, as opposed to system compensation which are often not as robust. Guidelines are provided to build a tailored CMOS ISFET array, emphasizing that the needs in terms of applications are the keys to selecting the right pixel architecture. Over the next few years, the race for the largest and densest array is likely to be put on hold to allow the research to focus on new pixel topologies, ultimately leading to the development of reliable and scalable arrays. A wide range of new applications are expected to motivate this paper for at least another decade. [ABSTRACT FROM PUBLISHER]

This paper introduces \mu-NET, a microfluidic LAN that supports the exchange of both digital information and biochemical information carried by droplets moving across molecular processors in a microfluidic chip. The \mu-NET can be used to support molecular biology applications like DNA, RNA, and protein biosynthesis. The \mu-NET is the first realization of a microfluidic networking paradigm that controls movements of droplets in microfluidic chips by exploiting hydrodynamic phenomena only and builds on recent solutions to achieve communications in the microfluidic domain. The \mu-NET integrates techniques to represent addressing information, as well as switching and medium access control solutions. In fact, in \mu-NET, the address of the molecular processor where a droplet should be sent to is encoded into the distance between droplets; switching is executed to steer the droplets inside the microfluidic device; medium access control is applied to avoid collisions between droplets that may result in their fusion and, thus, loss of the biochemical information. In this paper, the design of \mu-NET is presented in detail, and simulation results validating \mu-NET operations are shown. [ABSTRACT FROM PUBLISHER]

In vivo multi-target and selective concentration monitoring of neurotransmitters can help to unravel the brain chemical complex signaling interplay. This paper presents a dedicated integrated potentiostat transducer circuit and its selective electrode interface. A custom 2-electrode time-based potentiostat circuit was fabricated with 0.13 \mum CMOS technology and provides a wide dynamic input current range of 20 pA to 600 nA with 56 \muW, for a minimum sampling frequency of 1.25 kHz. A multi-working electrode chip is functionalized with carbon nanotubes (CNT)-based chemical coatings that offer high sensitivity and selectivity towards electroactive dopamine and non-electroactive glutamate. The prototype was experimentally tested with different concentrations levels of both neurotransmitter types, and results were similar to measurements with a commercially available potentiostat. This paper validates the functionality of the proposed biosensor, and demonstrates its potential for the selective detection of a large number of neurochemicals. [ABSTRACT FROM PUBLISHER]

The study of atmospheric chemistry-climate interactions is one of today's great computational challenges. Advances in the architecture of Graphics Processing Units (GPUs) in both raw computational power and memory bandwidth sparked the interest for General-Purpose computing on graphics accelerators in scientific applications. However, the introduction of GPUs in the High Performance Computing (HPC) landscape increased the complexity of software development, due to the inherent heterogeneity requirements of programming models and design approaches, creating a gap in uptake and attainable performance in the presently available scientific community codes. This paper provides an overview of the challenges encountered when using GPU accelerators to achieve optimal performance to calculate the kinetics of chemical tracers in climate models, the techniques used to address them and the insights gained from the process. The paper presents the development of a chemical kinetics code-to-code parser to automatically generate chemical kinetics calculations on three different generations of GPU accelerators (M2070, K80, and P100). The accelerated portion of the application achieves a speedup of up to 22×, equivalent to performance gains of +19 percent up to +90 percent compared with the processor-only version, when using a cluster of 8 Nodes with dual Intel E5-2680 v3 processor and a Kepler architecture (K80), allowing faster completion of the simulations. The paper also provides practical insights and relevant considerations for the development and acceleration of complex applications. [ABSTRACT FROM AUTHOR]

The halogen volatile organic compound (VOC) is a common industrial pollutant, mainly including trichloroethylene, dichloromethane, trichloroacetic acid, chloro-fluoro-carbons, carbon tetrachloride, trihalomethans, chlorodifuoromethanes, hydrofluorocarbons, and some other fluor alkaline, ether, and amine. The halogen VOCs have reproductive toxicity, immunotoxicity, and neurotoxicity. The traditional methods for treating them include masking method, dilution method, chemical oxidation method, incineration method, UV oxidation method, photocatalytic oxidation method, absorption method, and biological method. In this paper, advantages and disadvantages of traditional methods have been studied and analyzed. A new plasma technology has been put forward, which has the advantage of the rapid reaction to ambient temperature, wide applications, system compactness, simplicity of operation and short residual time, and the plasma technology is especially appropriate for the decomposition of VOCs. At present, as for the control of VOCs, the plasma technology has drawn much attention as an energy-saving technology. In this paper, the equipment for the decomposition of halogen VOCs has been analyzed, including the plasma rectors, power characteristics, operation conditions, and the decomposition mechanisms of C2HCl3, CH2Cl2, C2H3Cl3, CCl4, CHCl3, CF4, C2F6, and SF6 have been investigated and concluded. Finally, it is concluded that the combination of the plasma technology with traditional methods would be main direction of study in the future. [ABSTRACT FROM AUTHOR]

The processes of electrical charge accumulation and dissipation in dielectric materials are critical to spacecraft construction and operational anomaly resolution. Electrical conductivity, and therefore surface potential, of radiation-damaged materials undergoes unpredicted changes while on orbit. The space environment causes fundamental modifications in the chemical structure of spacecraft materials by breaking intermolecular bonds and creating free radicals that act as space charge traps. Over time, free radicals react with each other and the material recovers. The rates of free radical formation and loss determine the dynamics of the conductivity of spacecraft materials. Lack of knowledge about dynamic aging is a major impediment to accurate modeling of spacecraft behavior over its mission life. This paper presents an investigation of the chemical and physical properties of polyimide (PI) films during and after irradiation with high-energy (90 keV) electrons. The constant voltage method was utilized to monitor material conductivity during the recovery process. To quantify the concentration of free radicals within the irradiated material, the electron paramagnetic resonance technique was used. Changes in the infrared (IR) absorption profile of irradiated materials during the recovery process were identified using the directional-hemispherical reflectance technique coupled with the Fourier transform IR spectroscopy. This physical/chemical collaboration allowed correlation of chemical changes in PI with the dynamic nature of spacecraft material aging. [ABSTRACT FROM PUBLISHER]

Chemical algorithms are statistical control algorithms described and represented as chemical reaction networks. They are analytically tractable, they reinforce a deterministic state-to-dynamics relation, they have configurable stability properties, and they are directly implemented in state space using a high-level visual representation. These properties make them attractive solutions for traffic shaping and generally the control of dynamics in computer networks. In this paper, we present a framework for deploying chemical algorithms on field programmable gate arrays. Besides substantial computational acceleration, we introduce a low-overhead approach for hardware-level programmability and re-configurability of these algorithms at runtime, and without service interruption. We believe that this is a promising approach for expanding the control-plane programmability of software defined networks (SDN), to enable programmable network dynamics. To this end, the simple high-level abstractions of chemical algorithms offer an ideal northbound interface to the hardware, aligned with other programming primitives of SDN (e.g., flow rules). [ABSTRACT FROM AUTHOR]

Research on nanowire growth with patterned arrays of catalyst has shown that wire-to-wire spacing is an important factor affecting nanowire quality. To improve the process yield and the length uniformity of fabricated nanowires, it is important to reduce the resource competition between nanowires during the growth process. In this paper, we propose a physical-statistical nanowire-interaction model considering the shadowing effect and shared substrate diffusion area to determine the optimal pitch that would ensure the minimum competition between nanowires. A sigmoid function is used in the model, and the method of least squares is used to estimate the model parameters. The estimated model is then used to determine the optimal spatial arrangement of catalyst arrays. This work is an early attempt at the physical-statistical modeling of selective nanowire growth for the improvement of process yield. [ABSTRACT FROM AUTHOR]

In decades, the plasma ignition technology has drawn much attention due to its advantages. However, the numerical research on the plasma ignition of solid propellants is still limited. In this paper, a 1-D transient plasma ignition model of solid propellant is developed. A simplified chemical reaction mechanism of XM39 is employed in the model to explore the solid phase and gas phase chemical reactions and species transportations in the gas phase. The expansion process of the plasma jet is also investigated. The predicted surface pressure and ignition delay are compared to the experimental results. Good agreement with these data provides the necessary validation of the presented model. In the model, the calculated temperature profiles and the mass fraction distribution of the gas hexogen are used to characterize the reaction zone. In addition, the mass fraction distributions of CH2O and HCN are used to estimate the possibilities of different reaction paths. [ABSTRACT FROM AUTHOR]

This paper demonstrates and compares three configurations for ISFET arrays fabricated in unmodified CMOS that facilitate chemical imaging with linear pH-to-output conversion. Specifically, the typical voltage-mode source-follower configuration is compared against our recently proposed current-mode approach using an ISFET in velocity saturation. These two topologies are also compared against an extension of the current-mode topology to include a programmable-gate capacitor inside the pixel stack for offset compensation. Various performance metrics, such as linearity, speed, power consumption, size, attenuation, and noise have been experimentally measured to quantify the performance of each approach and a figure-of-merit (FoM) has been defined to capture the overall performance. Using this FoM, the current-mode approach results in the best overall performance. Through this paper, however, the relative merits and limitations of each approach are identified to be used as a guide for future designs which are usually application-specific. Furthermore, we illustrate methods used to obtain standard ISFET performance metrics in order to standardize the comparison of ISFET arrays using the figure-of-merit. [ABSTRACT FROM AUTHOR]

A large number of techniques have been developed to investigate magnetic nanoparticles for biomedical engineering applications to drug-delivery systems. In this paper, we carried out research into a new drug-release technology using liposomal nanoparticles equipped with magnetic controls. Exposures to magnetic fields were carried out using a permanent magnet (0.25 T) or an air-cored coil system (40 mT). Under exposure to the static field, anticancer flutamide (FM) in the liposomal membrane was excited by an emission wavelength of 325 nm. To compare the drug-release potentials with magnetic field effects on the behavior of FM in the model membranes, we measured the spectral changes with absorbance at 314, 260, and 370 nm after the excitation. Judging from the overall result of our liposomes prepared in this paper, up to 20 min after the excitation, the gradual increases in the drug-releases were relatively consistent with an S-T level intersystem crossing for a radical pair mechanism in equilibrium. Concerning the releases with magnetic field effects, the release rates obtained using a homogenous field of 0.25 T were more extensive on the order of 67%–75%, than those obtained at 0 T. Our system may provide the best possible balance between clinical performance and low invasivity. We believe the idea that magnetic fields are extremely suitable for the gentle control of chemical reactions. [ABSTRACT FROM AUTHOR]

To study how the fat affects the quantification of magnetic susceptibility of iron oxide nanoparticles (IONPs) according to the chemical shift effects, especially at ultra-short echo times, simulation experiments were carried out in this paper. Numerical phantom of IONPs solutions with six different concentrations was designed. Magnetic resonance imaging signals with different fat fractions (ffs) were generated according to a multi-peak chemical shift model. Quantitative susceptibility mapping (QSM) was calculated, and the relationship between the QSM value and ff, as well as echo selection, is evaluated. The results show that streaking artifacts become more and more severe when ff increases, which makes QSM value overestimated. Shortened echo spacing time can reduce streaking artifacts with the same ff. These findings will benefit future clinical evaluations for quantification of iron in vivo. [ABSTRACT FROM AUTHOR]

Chemical oxidation and the bactericidal capabilities of nonthermal plasma discharges can be used in different practical applications, such as biodecontamination, sterilisation of medical equipment, waste water treatment, syn-gas treatment, and others. In this paper, the oxidation and biodecontamination effects of impulsive plasma discharge, which propagate across a liquid sample/air interface (surface discharges), and through the bulk of a liquid sample (direct discharges), have been investigated. The oxidizing capability was analyzed by measuring the degree of decolorization of indigo carmine dye in water solutions. Gram-negative and gram-positive bacterias, E. coli and S. aureus, respectively, were used as model microorganisms in the investigation of the biocidal effects of plasma discharges. Surface and direct plasma discharges were generated by high-voltage impulses of both polarities, with the magnitudes of 20, 24, and 28 kV, and the chemical oxidation and biodecontamination capabilities of such discharges have been obtained and analyzed. It has been established that the defining factor in the chemical and biological effects of plasma discharges is the normalized delivered charge (dose). The results obtained in this paper show that surface discharges have greater biodecontamination capability as compared with direct transient plasma discharges. Also, it was shown that the decontamination rate of E. coli is more than double than that of S. aureus. [ABSTRACT FROM AUTHOR]

A pulsed discharge plasma (PDP) system with a multineedle-to-plate geometry electrode was applied in this paper to investigate the regeneration of granular activated carbon (GAC) spent with phenol in the PDP system. Regeneration percentage of the GAC under different conditions of initial solution conductivity and pH values was studied to clarify the regeneration of the GAC by the PDP. Formation of hydrogen peroxide (H2O2) with the same solution conditions was also investigated in this paper. The obtained results show that there was the same changing trend of GAC regeneration and H2O2 formation under different solution conditions, which clarify the critical effect of •OH on the GAC regeneration in the PDP system. The methods of scanning electron microscope (SEM), Brunauer–Emmett–Teller, Boehm titration, and Fourier transform infrared spectroscopy (FTIR) were used in this paper to demonstrate the medication of the GAC by the PDP treatment. The obtained results show that the regenerated GAC could recover a partial pore structure compared with the original GAC by the SEM analysis. The surface area, micropore volume, and total pore volume of the regenerated GAC increased, while the mesopore volume and the macropore volume decreased on the regenerated GAC; comparing with the original GAC, there was higher amount of acidic functional groups and lower amount of basic functional groups on the surface of the regenerated GAC; the intensities of O–H, C=C, C=O, and C–O enhanced significantly by the FTIR analysis. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the cycle-based sizing optimization for diesel-engine two-cell selective catalytic reduction (SCR) systems. In modeling the SCR system, it is generally assumed that the states inside the catalyst can are homogeneous to simplify the modeling work. However, the actual states are not homogeneous, and the modeling error becomes large if the catalyst length is long. To reduce the modeling error, the states are assumed piecewise homogeneous, i.e., the catalyst is sliced into multicells and the states for each cell are assumed homogeneous. In this paper, we focus on the two-cell SCR systems where the two cells are connected in series and where the chemical reaction rates are assumed identical for the two cells. Considering the main chemical reactions and assuming that each cell is a continuous stirred tank reactor, a nonlinear system model with six states is obtained. To simultaneously reduce the tailpipe \mboxNOx and ammonia slip, it is quite interesting to study the optimal control of the urea dosing such that the \mboxNOx emissions can be maximally converted and where the ammonia slip is constrained. A dynamic programming (DP) algorithm that has a tolerable computational load is proposed. Since the whole catalyst is sliced into two cells, the next motivation is how to divide the catalyst such that the \mboxNOx conversion efficiency can be maximized while meeting the tailpipe ammonia constraint. The best sizing ratio of the SCR system in our application for the US06 test cycle is found to be 60%–40%. [ABSTRACT FROM PUBLISHER]

The emergence of molecular communication has provided an avenue for developing biological nanonetworks. Synthetic biology is a platform that enables reprogramming cells, which we refer to as Bio-NanoThings, that can be assembled to create nanonetworks. In this paper, we focus on specific Bio-NanoThings, i.e, bacteria, where engineering their ability to emit or sense molecules can result in functionalities, such as cooperative target localization. Although this opens opportunities, e.g., for novel healthcare applications of the future, this can also lead to new problems, such as a new form of bioterrorism. In this paper, we investigate the disruptions that malicious Bio-NanoThings (M-BNTs) can create for molecular nanonetworks. In particular, we introduce two types of attacks: 1) blackhole and 2) sentry attacks. In blackhole attack M-BNTs emit attractant chemicals to draw-in the legitimate Bio-NanoThings (L-BNTs) from searching for their target, while in the sentry attack, the M-BNTs emit repellents to disperse the L-BNTs from reaching their target. We also present a countermeasure that L-BNTs can take to be resilient to the attacks, where we consider two forms of decision processes that includes Bayes’ rule as well as a simple threshold approach. We run a thorough set of simulations to assess the effectiveness of the proposed attacks as well as the proposed countermeasure. Our results show that the attacks can significantly hinder the regular behavior of Bio-NanoThings, while the countermeasures are effective for protecting against such attacks. [ABSTRACT FROM PUBLISHER]

Biofuel production as a sustainable source of green energy is considered a promising complement to petroleum in order to prevent environmental problems such as global warming. In this regard, microalgae can be one of the best options, since other plant resources may be used for human consumption and utilizing them for producing biofuel may cause an increase in their price. However, there are several challenges to extract oil from microalgae, e.g., high energy consumption, chemical solvents, and algae culture destruction, which should be addressed by new approaches. In this paper, we suggest nanosecond pulse electric field as a physical method for hydrocarbon extraction from microalgae. Botryococcus braunii with high hydrocarbon production potential was used as the microalga model. To obtain an effective extraction, nsPEFs with 87.5-kV/cm electric field, 200-ns pulse duration, 0.3-J/pulse energy, 1-Hz pulse repetition frequency, and 1–50 pulses were applied. Microscopic observations with image processing and chemical assessments were performed for analyzing the samples, understanding the extraction mechanisms, and comparing the outcomes. According to the results, 50 pulses with 16.7-J/mL energy consumption were sufficient for oil extraction, showing that the pulsed power approach can be used as an appropriate physical method for extracting oil from Botryococcus braunii. [ABSTRACT FROM AUTHOR]

During hypersonic flights of a space vehicle, shock heating ionizes the molecules of the surrounding air, which will create a plasma sheath that covers all or part of the vehicle. The plasma sheath absorbs and reflects electromagnetic (EM) waves, resulting in communication blackout of the installed electronic devices or systems. Moreover, when a high-power microwave (HPM) illuminates the moving vehicle, the constituent parameters of the plasma sheath will be altered since the plasma covering absorbs part of the energy of the HPM. In consequence, the transmission and scattering properties of the high-speed vehicle to the EM communication signals are changed. In order to investigate the complicated interactions among the plasma sheath, the HPM, and the low-power communication EM signals, a multiphysics model based on the computational fluid dynamics and the computational EMs is proposed, and the corresponding numerical solution is provided as well. Since the primary aim of the paper is to reveal the multiphysics method and relevant phenomenon, both the theoretical derivations and numerical examples are only presented in the 2-D space. [ABSTRACT FROM AUTHOR]

Milk adulteration is one of the most dishonest food preparation, which not only reduces the nutritional value but also causes various diseases to human. Some of the common adulterants are detergents, ammonium sulphate [(NH4)2SO4], sodium hydroxide (NaOH), sodium-bi-carbonate (NaHCO3), and common salt (NaCl). The aim of this paper is to identify the minimum detectable limit for the above five adulterants in milk. An impedance sensor is used, which is sensitive to the ionic concentration of the measuring medium and gives different phase angle of the impedance, when immersed in different adulterated/unadulterated milk. Signal transduction circuit is designed to convert the phase angle to voltage and for display in liquid crystal display. By this detection system, the limit of detection of adulterants in milk with different fat % (from 1.5% to 20%) is studied. Commercial packet milk, ultra high temperature milk, and raw-milk (directly collected from the milk collection center) are used for the experiment. Experimental results are plotted in origin software and statistical analysis method analysis of variance is applied on experimental data for verification of the result and to check the data consistency. [ABSTRACT FROM PUBLISHER]

The lack of medical salt aerosssol concentration detection method and instability powder atomization result in poor aerosol inhalation treatment effects. Considering medical vaporizer specific requirements, physical and chemical characteristics of salt powder commonly used, this paper analyzes salt particle light scattering using T-matrix method based on discrete source, calculated scattering intensity of salt particle with diameter of 0.4 to 6~\mu \textm , develops photoelectric salt aerosol concentration sensor with forward differential scattering light path and weak current signal conditioning circuits. Sensor salt aerosol concentration calibration experiments and performance tests was carried out, and the results show as follows: the maximum residuals of sensor is 0.262 mg/L in calibration experiments and relative error in performance tests was 12.9%, satisfied salt aerosol concentration detection requirements and could provide basis for on line stability control of aerosol concentration in medical salt powder atomization process. [ABSTRACT FROM PUBLISHER]

The high nitrogen oxide (\textNO_x) emission is one of the main issues for diesel engines. To reduce the \text NO_x emissions with an after-treatment system, the information of NO and NO2 concentrations plays an important role. In this paper, we investigate the NO and NO2 concentration estimation for a diesel-engine-after-treatment system with \textNO_x sensor measurements. The main objective is to estimate the NO and NO2 concentrations after diesel particulate filter (DPF) such that the selective catalytic reduction system can be benefited from the estimated concentrations. Since the diesel oxidation catalyst (DOC) is connected in series with DPF, the estimation work for DOC is also necessary. An empirical engine-out NO2/ \textNO_x ratio model is adopted to predict the inputs of DOC. By considering the main chemical reactions inside DOC and DPF, the NO and NO2 concentration models are obtained. The nonlinear models are converted into linear-parameter-varying forms. Then, a gain-scheduling Luenburger observer is proposed for the DOC and DPF. A practical assumption in which the system modeling and sensor measurements are not perfectly precise is made. Therefore, the gain-scheduling Luenburger observer does not directly share the weighting factors of the original system. By defining the estimation error, an augmented compact system is obtained. Both the stability and the energy-to-peak performance are investigated for the compact system. Based on the derived conditions, the observer design approach is proposed. Experimental studies and comparisons are given to validate the results. Compared with an existing work, the designed observer can improve the estimation performance significantly. [ABSTRACT FROM PUBLISHER]

While ISI is a common issue in classical communications, it is more challenging and prominent in the context of molecular communication, because one cannot readily combat ISI with classical channel equalization techniques. This is due to the fact that transmitter can only release a positive amount of concentration of a specific molecule into the medium. Previous works have proposed use of chemical reactions to remove molecules from the environment, and to effectively simulate negative signals. However, the differential equation describing a diffusion-reaction process is non-linear. This precludes the possibility of using Fourier transform tools. In this paper, a solution for simulating negative signals based on the diffusion-reaction channel model is proposed. While the proposed solution does not exploit the full degrees of freedom available for signaling in a diffusion-reaction process, but its end-to-end system is a linear channel and amenable to Fourier transform analysis. Based on our solution, a modulation scheme and a precoder are introduced and shown to have a significant reduction in error probability compared with previous modulation schemes, such as concentration shift keying (CSK), pre-equalization, depleted-molecule shift keying (D-MoSK), and molecular concentration shift keying (MCSK). The effects of various imperfections (such as quantization error) on the communication system performance are studied. [ABSTRACT FROM AUTHOR]

In order to study the total ionizing dose degradation and enhanced low dose rate sensitivity effect for semiconductor devices in the space environment, we simulate the drift-diffusion-reaction processes in a 3-dimensional SiO2–Si system. Since the time scale of the drift-diffusion processes is much larger than that of the chemical reaction processes, we use a multi-time-step algorithm to calculate the two types of processes, respectively. In this paper, partial differential equations used to describe the electrodiffusion processes are solved by a finite element method, while the chemical reactions taking place independently in every mesh node are solved as ordinary differential equations. We reproduce qualitative properties of total ionizing dose effect and compare our numerical results with experimental data and other simulation results. This paper paves a way for 3-D simulation of total ionizing dose and enhanced low dose rate sensitivity with high efficiency and robustness. [ABSTRACT FROM PUBLISHER]

Currently, DNA strand displacement is often used to build neural networks or solve logical problems. While there are few studies on the use of DNA strand displacement to solve the higher order equations. In this paper, the catalysis, degradation, annihilation and adjusted reaction modules are built through DNA strand displacement. The chemical reaction networks of the corresponding higher order equations and simultaneous equations are established through these modules, and these chemical reaction networks can be used to build analog circuits to solve binary primary simultaneous equations and binary quadratic simultaneous equations. Finally, through Visual DSD software verification, this design can realize the solution of binary primary simultaneous equations and binary quadratic simultaneous equations, which provides a reference for DNA computation in the future. [ABSTRACT FROM AUTHOR]

The components with molecular communication (MC) functionalities can bring an opportunity for emerging applications in fields from personal healthcare to modern industry. In this paper, we propose the designs of the microfluidic transmitter and receiver with quadruple concentration shift keying (QCSK) modulation and demodulation functionalities. To do so, we first present an AND gate design, and then apply it to the QCSK transmitter and receiver design. The QCSK transmitter is capable of modulating two input signals to four different concentration levels, and the QCSK receiver can demodulate a received signal to two outputs. More importantly, we also establish a mathematical framework to theoretically characterize our proposed microfluidic circuits. Based on this, we first derive the output concentration distribution of our proposed AND gate design, and provide the insight into the selection of design parameters to ensure an exhibition of desired behavior. We further derive the output concentration distributions of the QCSK transmitter and receiver. Simulation results obtained in COMSOL Multiphysics not only show the desired behavior of all the proposed microfluidic circuits, but also demonstrate the accuracy of the proposed mathematical framework. [ABSTRACT FROM AUTHOR]

In this paper, for the first time we demonstrate zero-power volatile-organic-chemical (VOC) detectors based on micromechanical switches suitable for plant health monitoring. Differently from state-of-the-art active chemical sensors, the device presented here exploits a completely passive, chemically-sensitive switch based on a bimaterial micro-cantilever and a passive switch-based readout mechanism to detect VOCs exceeding a pre-determined concentration released by unhealthy plants. When exposed to target VOCs, the polymer/metal bimaterial beam bends downward and trigger the switch due to the stress induced from the absorption of chemicals in the polymer layer. Here we show experimental demonstrations of detecting toluene, hexenol (cis-3-Hexen-1-ol, a chemical released from plants under attack by pests) and ethanol, respectively, with our fabricated prototypes. The demonstrated high sensitivity to ethanol (~8 nm/ppm) and hexenol (~3.3 nm/ppm) was achieved by the optimization of device geometries showing a great promise of the proposed technology to ultimately achieve 10s ppm detection limit (with a sub-micron contact gap and voltage bias) which is required for the device operation in close proximity to a plant in an open environment. [2020-0190] [ABSTRACT FROM AUTHOR]

Searching similar graphs in graph databases for a query graph has attracted extensive attention recently. Existing works on graph similarity queries are threshold based approaches which return graphs with distances to the query smaller than a given threshold. However, in many applications the number of answer graphs for the same threshold can vary significantly for different queries. In this paper, we study the problem of finding top- $k$ k most similar graphs for a query under the distance measure based on maximum common subgraph (MCS). Since computing MCS is NP-hard, we devise a novel framework to prune unqualified graphs based on the lower bounds of graph distance, and accordingly derive four lower bounds with different tightness and computational cost for pruning. To further reduce the number of MCS computations, we also propose an improved framework based on both lower and upper bounds, and derive three new upper bounds. To support efficient pruning, we design three indexes with different tradeoffs between pruning power and construction cost. To accelerate the index construction, we explore bound relaxation techniques, based on which approximate indexes can be efficiently built. We conducted extensive performance studies on real-life graph datasets to validate the effectiveness and efficiency of our approaches. [ABSTRACT FROM AUTHOR]

SF 6 /N 2 mixtures is considered as a practical alternative proposal of SF 6 in GIS and GIL. Simulating particle transportations and chemical reactions during the positive streamer propagation in SF 6 /N 2 mixtures assists in the insulation performance optimization of SF 6 /N 2 mixtures. This paper presents a fluid dynamic model coupled with the chemical reaction system for the positive streamer propagation in SF 6 /N 2 mixtures. The Townsend coefficients of the 20%SF 6 /80%N 2 mixture derived from the proposed chemical reaction system are in accordance with the measurement results. Based on this model, the propagation of the positive streamer in a 1 mm needle-plate gap in the 20%SF 6 /80%N 2 mixture is simulated. Simulated results indicate that there exists a negative space charge region in the streamer channel. It can be attributed to the increasing attachment rates of SF 6 yielding SF 5 − and SF 6 −, and the reduction of the ionization rates of N 2 and SF 6 in the streamer channel. Besides, it is noted that the ionization activities of N 2 and SF 6 at the streamer head are equally important to support the continuous propagation of the positive streamer. The ionization of N 2 in the streamer channel serves as an important factor to supply electrons and avoid the accumulation of the negative space charge. [ABSTRACT FROM AUTHOR]

The introduction of large-scale chemical sensing systems in CMOS which integrate millions of ISFET sensors have allowed applications such as DNA sequencing and fine-pixel chemical imaging systems to be realised. Using CMOS ISFETs provides advantages of digitisation directly at the sensor as well as correcting for non-linearity in its response. However, for this to be beneficial and scale, the readout circuits need to have the minimum possible footprint and power consumption. Within this context, this paper analyses an ISFET based pH-to-time readout using an inverter in the time-domain as a level-crossing detector and presents a 32 × 32 array with in-pixel digitisation for pH sensing. The inverter-based sensing pixel, controlled by a triangular waveform, converts the pH response into a time-domain signal whilst also compensating for sensor offset and thus resulting in an increase in dynamic range. The sensor pixels interface to a 15-bit asynchronous column-wise time-to-digital converter (TDC), enabling fast asynchronous conversion whilst using minimal silicon area. Parallel outputs of 32 TDC interfaces are serialised to achieve fast data throughput. This system is implemented in a standard 0.18 $\,\mu$ m CMOS technology, with a pixel size of 26  $\mu$ m × 26  $\mu$ m and a TDC area of 26  $\mu$ m × 180  $\mu$ m. Additionally, we investigate the use of additional offset compensation by having half of the array implemented with the floating gate tied down via a well diode. Measured results demonstrate the system is able to sense reliably with an average pH sensitivity of 30 mV/pH, whilst being able to compensate for sensor offset by up to $\pm$ 7 V. A resolution of 0.013 pH is achieved and noise measurements show an integrated noise of 0.08 pH within 2–500 Hz and SFDR of 42.6 dB. The total power consumption of the system is measured to be 11.286 mW when operating at a high frame rate of 1 KFPS. [ABSTRACT FROM AUTHOR]

Excess limit of Nitrites, which are prevalent within environmental and physiological systems, have severe detrimental effects, thus point-of-source detection becomes an important requirement to take suitable preventive measures. This paper presents the design and development of a standalone, point-of-source, portable, low-cost, automated and integrated microfluidic system for quick detection and quantification of nitrite. Based on multiphysics simulations, a disposable polydimethylsiloxane (PDMS) microfluidic device was employed to carry out the controlled Griess reaction based assay. A low-cost 3D printed syringe pump was developed to inject the sample and reagent. Photometric detection was employed using light emitting diode (LED) and photodiode. A transimpedance amplifier circuit was designed and fabricated to achieve amplified photodiode output with reduced noise. An off-the-shelf microprocessor was used to integrate the whole system and a smartphone application (app) was developed to control the complete system and store the data. Interaction between the application and the microprocessor was achieved using Bluetooth connectivity. Spectrophotometric validation was performed and a calibration equation was obtained which was used to convert the device voltage output to absorption, through specially programmed android app. All the components were integrated in a 3D printed platform whose virtues such as ease of usage and affordability makes, quantification of nitrite, a simple and real time process wherein the limit of detection and limit of quantification values are found to be 0.07103 ppm and 0.21524 ppm respectively with good repeatability. [ABSTRACT FROM AUTHOR]

Rhythmic oscillation is crucial for information transmission and neural communication among different brain areas. Stochastic resonance (SR) can evoke different patterns of neural oscillation. However, the characteristics of network resonance and underlying dynamical mechanisms are still unclear. In this paper, a biological model of cortical network is established and its dynamical response to external periodic stimulation is investigated. We explore the oscillatory resonance of excitatory and inhibitory populations in cortical network. It is found that the intrinsic parameters of neural populations determine the extent of resonant activity, indicating that the firing rate exhibits coherent oscillation when the frequency of external stimulation is close to intrinsic frequency of neural population. In addition, the nonlinear dynamics of cortical network in oscillatory resonance can be represented by helical manifolds in low-dimensional state space. The geometry of neural manifolds reveals the periodic dynamics and state transition in oscillatory resonance. Moreover, time delay in chemical synapses can induce multiple resonances, which appear intermittently at integer multiples of the period of input signal. The dynamical response of neural population achieves maximal periodically, due to the transition of network states induced by time delay. Furthermore, mean-field theory is applied to analyze theoretical dynamic of cortical networks with time delay and demonstrate the effective transmission of stimulation information via oscillatory resonance in the brain. Consequently, the obtained results contribute to the improvement of neuromodulation for neurological disease from the viewpoint of the neural basis. [ABSTRACT FROM AUTHOR]